Steady-state Behavior Research Articles

Modeling steady state rate- and temperature-dependent strain hardening behavior of glassy polymers

In this paper, we use molecular dynamics (MD) simulations to investigate the origin of strain hardening in glassy polymers, with a particular focus on the influences of strain rate and temperature. We demonstrate that strain hardening in uniaxial tension arises from bond stretching and is relaxed by bond rotation, characterized by the evolution of dihedral angles. Based on this rotational relaxation, strain rate plays a role analogous to temperature, resulting in a steady state behavior in the hardening region identifiable by strain rate and temperature. Following these observations, we propose a constitutive model to describe the rate- and temperature-dependent strain hardening behavior of glassy polymers using a viscous potential as a function of strain rate. To capture the elastic and yield behavior at small strains, we integrate this viscous potential with a conventional elasto-viscoplastic (EVP) model, giving rise to our V-EVP model. The V-EVP model is shown to be thermodynamically consistent and is validated by comparison to MD simulation results of glassy polymers undergoing uniaxial tension tests across a broad range of temperatures and strain rates.

Neural network-based prescribed performance tracking control for a class of nonlinear systems with mismatched disturbances

This paper addresses the prescribed performance tracking control problem for a class of nonlinear systems subject to mismatched uncertainties. A novel disturbance observer-based control (DOBC) scheme is proposed through combining radial basis function neural network (RBFNN) and prescribed performance function (PPF). In contrast to traditional DOBC, the proposed approach employs RBFNN technology to approximate unknown nonlinear functions in the system, instead of treating them as part of lumped disturbances. A novel disturbance observer is developed to estimate disturbances characterised by a nonlinear exogenous system. To enhance control performance, a PPF that characterises both transient and steady-state behaviour is used for the transformation of tracking errors. It can be proved that all the states of the closed-loop system can be guaranteed to be uniformly ultimately bounded (UUB), and that the tracking error evolves within the prespecified boundaries. Theoretical results are validated and supported by two simulation examples.

A new formulation of the understeer gradient and stability margin to analyse vehicle steady-state cornering behaviour

The understeer gradient is a measure that describes a vehicle's cornering behaviour as either understeer, neutral, or oversteer. Several formulations of this measure have been developed, all of which are reviewed in this paper. It has been found that all of these formulations rely essentially on the lateral acceleration of the vehicle. While the understeer gradient provides a useful connection to vehicle stability, its reliance on lateral acceleration can result in numerical instability and error at high levels of lateral acceleration. To address this issue, a new formulation of the understeer gradient is proposed in this paper. This new formulation is based on vehicle speed and is suitable for all maneuvers. Unlike previous formulations, it does not rely on lateral acceleration or provide a direct connection to vehicle stability. To address the issue of vehicle stability, a new measure called the stability margin is also proposed in this paper. The stability margin provides a more precise measurement of a vehicle's stability than the understeer gradient alone. By combining the stability margin with the new formulation of the understeer gradient, a more comprehensive picture of a vehicle's cornering behaviour and stability can be obtained.

Control of combustion distributions in compression-ignition engines using rate-constrained model predictive control with reference preview

To support the transition toward sustainable alternative fuels, advanced combustion control strategies can enable operation of compression-ignition engines with a wide range of fuels under challenging inlet conditions. This work presents a rate-constrained model predictive controller that uses state estimate feedback and integral tracking to control combustion phasing distributions by coordinating fuel injection timing with the power supplied to an electrically heated in-cylinder ignition assist device. The controller was validated in simulation using a statistical virtual engine that replicates both transient and steady-state stochastic combustion behavior. This virtual engine was tuned with data from experiments conducted at a low pressure-temperature inlet condition that induced highly variable combustion behavior akin to operating with a low cetane fuel. The controller achieves rapid tracking of combustion phasing step commands by supplying ignition assist power when needed to support fuel injection timing. All the while, it maintains closed-loop combustion variability at less than 6% higher than the open-loop system variability, and enforces ignition assist power range and rate constraints to reduce thermo-mechanical stress on the actuator. Furthermore, reference tracking is ensured even if combustion sensitivity to the ignition assist actuator deviates by as much as 83% from the controller’s internal model, without the need for retuning control parameters. Finally, the controller can coordinate actuators early and speed up tracking when a reference trajectory is previewed ahead of time, and its horizons can be tuned in a manner that maintains desirable control performance without compromising on computational tractability.

Nitrogen addition alleviates water loss of Moso bamboo (Phyllostachys edulis) under drought by affecting light-induced stomatal responses

The combined climate-change-evoked drought and nitrogen (N) deposition have severely affected plant carbon and water relations governed by stomata. However, the interplay between steady-state and dynamic stomatal behavior responses to light remains unclear regarding its impact on plant water and carbon relations. The objective here was to investigate whether light-induced stomatal dynamics could mitigate the adverse effects of steady-state gas exchange on water conservation or photosynthesis under drought and N addition conditions. We conducted a manipulative experiment to investigate the impacts of throughfall reduction, N addition, and their combination on light-induced stomatal and photosynthetic dynamics in a Moso bamboo (Phyllostachys edulis) forest. We determined the influence of stomal response rate on water loss and photosynthesis, and further assessed whether it mitigated the effects of steady-state gas exchange (gs). We found that Moso bamboo decreased gs under throughfall reduction, while accelerated stomatal opening and biochemical activation when irradiance increased, which reduced the lag in photosynthesis during the induction period. In contrast, under the combined throughfall reduction and N addition condition, Moso bamboo increased gs but showed faster stomatal closure, which decreased the percentage of transpiration following a decrease in light intensity. Our findings indicate that stomatal dynamic behavior may depend on the effects of steady-state gas exchange on water conservation and carbon uptake under different soil water and N conditions. These discoveries contribute to our understanding of the coupling mechanisms of plant water use and carbon uptake in the context of global changes.

Full state observer-based pole placement controller for pulse width modulation switched mode voltage-controlled buck Converter

Switched mode DC-DC converters play an important role in today's renewable energy systems, electric Vehicles, consumer electrical appliances, and many more. While many researchers have designed controllers for DC-DC converters, achieving low implementation cost remains a significant hurdle. This paper proposes a cost-effective observer-based pole placement controller for a PWM voltage-controlled Buck converter with clear step by step design approach. The state space averaged model of the DC-DC power converter is used to design pole placement with integrator compensator and full state observer. Pole placement is employed to improve the transient and steady state behavior of Voltage reference tracking response and full state observer is applied to extract the inductor current with the aim of removing the actual current sensor. Design specifications are set to a settling time of less than 5 msec and an overshoot of less than 5 %. While designing Observer-Controller combination, the separation principle, designing the controller and observer independently, is utilized by placing the observer poles far to the left of the controller poles for the Observer to converge faster. The designed controller and observer is verified with simulation in MATLAB/SIMULINK software and design of developed controller and observer are realized using low-cost analog electronics circuit components The results shows that the proposed system's strength in tracking the reference output voltage even in the presence of input voltage disturbance and the mean value of inductor current is well extracted having only the output voltage and MOSFET gate signal.

Investigating the Photophysical Aspects of a Naphthalene-Based Excited-State Proton Transfer Dye 1-(1H-Benzo[d]imidazol-2-yl)naphthalen-2-ol: pH-Dependent Modulation of Photodynamics.

The steady state and time-resolved photophysical behavior of a proton transfer dye 1-(1H-benzo[d]imidazol-2-yl)naphthalen-2-ol (H-BINO) was investigated. The excited state intramolecular proton transfer (ESIPT) reaction in H-BINO is predominant in nonpolar solutions (toluene and DCM) with a lifetime of ∼1.0 ns. However, in polar media (DMF and MeOH), the excited state photodynamics is characterized by a complex equilibrium of emission from the locally excited state (0.1-2.3 ns), the phototautomer (0.5-1.2 ns), and the anionic emission (2.1-5.4 ns). In the solid state, emission from the various aggregated states dictates the photobehavior. Interestingly, the photodynamics in aqueous solution changes starkly as a function of pH with the anionic (2.1 ns) and phototautomeric (0.5-1.0 ns) emissions guiding the photodynamics as the pH of the medium increases. Optimized structural parameters at the proton donor and acceptor sites for the enol and keto forms and the calculated potential energy curve along the proton transfer coordinate at the density functional theory (DFT) level with the B3LYP/6-311G++(d,p) theory support a favorable and barrierless ESIPT process. The current results will surely boost the ongoing research on small molecule emissive materials.

Microflow sensing and control using an in-channel birefringent biomembrane.

This study describes the function, optimization, and demonstration of a new class of passive, low-cost microfluidic flow meters based on birefringent chitosan biomembranes analyzed by polarized microscopy. We subjected the membrane to dynamic flow conditions while monitoring the real-time response of its optical properties. We obtained figures of merit, including the linear response operating range (0 to 65 μL min-1), minimum response time (250 ms), sensitivity (2.03% × 10-3 μL-1 min), and minimum sensor longevity (1 week). In addition, possible sources of interference were identified. Finally, we demonstrate the membrane as a low-cost flow rate measurement device for the close loop control of a commercial pressure-driven pump. Preliminary experiments using a basic PID controller with the membrane-based flow rate measurement device showed that stable control could be achieved and the system could reach steady-state behavior in less than 15 seconds. Analysis of fundamental limits to sensor response time indicate the potential for faster steady-state behaviour.

Field-induced magnetorheological study towards the active magneto-viscoelastic behavior of stable MnFe2O4 magnetic nanofluid

This work presents the fine-tuned synthesis of MnFe2O4 oleic acid-coated magnetic nanoparticles (MNPs) by the chemical co-precipitation method. The X-ray photoelectron spectroscopy (XPS) was utilized to investigate the elemental composition and oxidation state of oleic acid-coated MnFe2O4 MNPs. The Fourier transform infrared spectroscopy (FTIR) spectra were used to confirm the functional groups in the oleic acid-coated MnFe2O4 magnetic nanoparticles. The spherical shape of MnFe2O4 MNPs is confirmed by Field emission scanning electron microscopy (FESEM) and High-resolution transmission electron microscopy (HRTEM) techniques. Zeta potential (ζ) measurements were performed to confirm the stability of MnFe2O4 magnetic nanofluid (MNF). Magnetic measurements (M−vs−H) reveal the saturation magnetization, Ms = 20.3 emu/g and coercivity, HC = 30 Oe, confirming the single domain superparamagnetic nature at 300 K. Field-induced shear thinning behavior of the MnFe2O4 magnetic fluid is confirmed by a power law, η = c γn + n∞ and steady-state behavior measurements. Magneto viscous effect initially increased at a low shear rate of 20 s−1 and then decreased at a higher shear rate of 100 s−1, which confirms the stability of the MnFe2O4 magnetic fluid. Also, the highest deflection angle, θ = 243 m.rad of MnFe2O4 magnetic fluid was observed at a moderate shear rate 100 s−1 and a high magnetic field of 1.2 T, while the lowest value of deflection angle, θ = 65 m.rad was observed in the absence of magnetic field. In contrast, the storage modulus (G') is greater than the loss modulus (G''), in corroboration with the viscoelastic-to-viscous behavior of MnFe2O4 magnetic fluid.

A resource-based mechanistic framework for castration-resistant prostate cancer (CRPC)

Cancer therapy often leads to the selective elimination of drug-sensitive cells from the tumour. This can favour the growth of cells resistant to the therapeutic agent, ultimately causing a tumour relapse. Castration-resistant prostate cancer (CRPC) is a well-characterised instance of this phenomenon. In CRPC, after systemic androgen deprivation therapy (ADT), a subset of drug-resistant cancer cells autonomously produce testosterone, thus enabling tumour regrowth. A previous theoretical study has shown that such a tumour relapse can be delayed by inhibiting the growth of drug-resistant cells using biotic competition from drug-sensitive cells. In this context, the centrality of resource dynamics to intra-tumour competition in the CRPC system indicates clear scope for the construction of theoretical models that can explicitly incorporate the underlying mechanisms of tumour ecology. In the current study, we use a modified logistic framework to model cell–cell interactions in terms of the production and consumption of resources. Our results show that steady state composition of CRPC can be understood as a composite function of the availability and utilisation efficiency of two resources-oxygen and testosterone. In particular, we show that the effect of changing resource availability or use efficiency is conditioned by their general abundance regimes. Testosterone typically functions in trace amounts and thus affects steady state behaviour of the CRPC system differently from oxygen, which is usually available at higher levels. Our data thus indicate that explicit consideration of resource dynamics can produce novel and useful mechanistic understanding of CRPC. Furthermore, such a modelling approach also incorporates variables into the system’s description that can be directly measured in a clinical context. This is therefore a promising avenue of research in cancer ecology that could lead to therapeutic approaches that are more clearly rooted in the biology of CRPC.

Thermal State Effects on Potential Augmentation of the Ampacity of a Medium Voltage Underground Cable in Power Distribution: A Case Study

Thermal State Effects on Potential Augmentation of the Ampacity of a Medium Voltage Underground Cable in Power Distribution: A Case Study

Computationally efficient robust adaptive filtering algorithm based on improved minimum error entropy criterion with fiducial points

Recently, there has been a strong interest in the minimum error entropy (MEE) criterion derived from information theoretic learning, which is effective in dealing with the multimodal non-Gaussian noise case. However, the kernel function is shift invariant resulting in the MEE criterion being insensitive to the error location. An existing solution is to combine the maximum correntropy (MC) with MEE criteria, leading to the MEE criterion with fiducial points (MEEF). Nevertheless, the algorithms based on the MEEF criterion usually require higher computational complexity. To remedy this problem, an improved MEEF (IMEEF) criterion is devised, aiming to avoid repetitive calculations of the aposteriori error, and an adaptive filtering algorithm based on gradient descent (GD) method is proposed, namely, GD-based IMEEF (IMEEF-GD) algorithm. In addition, we provide the convergence condition in terms of mean sense, along with an analysis of the steady-state and transient behaviors of IMEEF-GD in the mean-square sense. Its computational complexity is also analyzed. Simulation results demonstrate that the computational requirement of our algorithm does not vary significantly with the error sample number and the derived theoretical model is highly consistent with the learning curve. Ultimately, we employ the IMEEF-GD algorithm in tasks such as system identification, wind signal magnitude prediction, temperature prediction, and acoustic echo cancellation (AEC) to validate the effectiveness of the IMEEF-GD algorithm.

Computing the solution trajectories, steady state approximation, and sensitivity analysis in complex chemical reaction mechanism

Ordinary differential equations are often employed in chemical kinetics mathematical modeling. The theoretical results for a model of a multi-step chemical kinetic process are presented in this article. This model seeks to describe both the complicated kinetics of complex chemical processes and the steady state behavior of chemical species. Reduction techniques are used to divide fast and slow processes according to their time scales, which simplifies the model. As a result, the quick processes are removed, making the slow processes the main emphasis of a reduced-dimensional model. The paper concentrates on a two-step reversible reaction mechanism for model reduction, which reduces the complexity of the entire reaction process. The phase flow of solution trajectories close to equilibrium points is also given special consideration in the analysis as it offers a clear and pertinent depiction of the behavior of the system. The physical properties of the observed data are further shown via MATLAB simulations. Sensitivity analysis computes parameters, revealing their impact on species behavior, visually presenting the parameter impact.

Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes

Long-run average optimization problems for Markov decision processes (MDPs) require constructing policies with optimal steady-state behavior, i.e., optimal limit frequency of visits to the states. However, such policies may suffer from local instability in the sense that the frequency of states visited in a bounded time horizon along a run differs significantly from the limit frequency. In this work, we propose an efficient algorithmic solution to this problem.

The steady behavior of the supercritical carbon dioxide natural circulation loop

The steady state behavior of thermodynamically supercritical natural circulation loops (NCLs) is investigated in this work. Experimental steady state results with carbon dioxide are presented for supercritical pressures in the range of 80–120 bar, and temperatures in the range of 20–65 °C. Distinct thermodynamic states are reached by traversing a set of isochors. An equation for the prediction of the steady state of NCLs at supercritical pressures is presented, and its performance is assessed using empirical data. Changes of mass flow rate as a result of independent changes of thermodynamic state, heating rate, driving height and viscous losses are shown to be accurately captured by the proposed equation. Furthermore, close agreement between the predicted and measured mass flow rate is found when the measured equipment losses are taken into account for the comparison. Subsequently, the findings are put forward in aid of the development of safe, novel supercritical natural circulation facilities.

Serendipitous Archival Observations of a New Ultradistant Comet C/2019 E3 (ATLAS)

We identified a new ultradistant comet C/2019 E3 (ATLAS) exhibiting preperihelion cometary activity at heliocentric distances ≳20 au, making it the fourth member of this population after C/2010 U3 (Boattini), C/2014 UN271 (Bernardinelli–Bernstein), and C/2017 K2 (PANSTARRS). From serendipitous archival data, we conducted analyses of the comet, finding that the activity was consistent with steady-state behavior, suggestive of sublimation of supervolatiles; that the cross section of dust increased gradually on the inbound leg of the orbit, varying with heliocentric distances as rH−1.5±0.4 ; and that the dust was produced at a rate of ≳102 kg s−1 within the observed timespan. Our modeling of the largely symmetric morphology of the comet suggests that the dust environment was likely dominated by mm-scale dust grains ejected at speeds ≲0.4 m s−1 from the sunlit hemisphere of the nucleus. Assuming a typical geometric albedo of 0.05 and adopting several simplistic thermophysical models, we estimated the nucleus to be at least ∼3 km across. We also measured the color of the comet to be consistent with other long-period comets, except being slightly bluer in g − r. With our astrometric measurements, we determined an improved orbit of the comet, based upon which we derived that the comet is dynamically new and that its perihelion distance will further shrink due to the Galactic tide. We conclude the paper by comparing the known characteristics of the known ultradistant comets.

Multiscale Finite Element Modeling of the Effect of Macro-Encapsulated Phase-Change Materials on the Thermal Performance of Hydronic Floor Heating Systems

Phase-change materials (PCMs) are commonly employed in building service equipment to regulate indoor temperatures and reduce energy consumption. This study conducted multi-scale finite element modeling to analyze the steady-state and dynamic thermal behavior of a hydronic radiant floor heating system integrated with macro-encapsulated PCMs. It predicted performance values for hydronic floor heating with and without macro-encapsulated PCMs. The study assessed the impact of the PCM volume fraction, heating water temperature, capsule thermal conductivity, and shape on the thermal performance of hydronic floor heating through various finite element models. The predictive capability of the finite element model was validated using experimental data, showing good agreement. Although the inclusion of PCMs lowered the floor temperature, it improved temperature distribution and retained heat when the system was inactive. The PCM volume fraction significantly influenced the performance of the hydronic floor. However, the shape of the macro-encapsulated PCM and thermal conductivity of the shell had minimal effects in the studied case. For instance, increasing the thermal conductivity of the shell of the PCM capsule fifty times from 0.3 to 15 W m−1 K−1 resulted in an increase in surface temperature by 1.2 °C.

USING FUZZY LOGIC CONTROLLER FOR A TWO- TANK LEVEL CONTROL SYSTEM

This paper presents a fuzzy logic controller for a two-tank level control system, which is a process with a dead time. The fuzzy controller is a proportional-integral (PI-like) fuzzy controller which is suitable for steady state behavior of the system. Transient behavior of the system was improved without the need for a derivative action by suitable change in the rule base of the controller. Simulation results showed the step response of the two-tank level control system when this controller was used to control this plant and the effect of the dead time on the response of the system.

Prolonged hysteresis in the Kuramoto model with inertia and higher-order interactions.

The inclusion of inertia in the Kuramoto model has long been reported to change the nature of a phase transition, providing a fertile ground to model the dynamical behaviors of interacting units. More recently, higher-order interactions have been realized as essential for the functioning of real-world complex systems ranging from the brain to disease spreading. Yet analytical insights to decipher the role of inertia with higher-order interactions remain challenging. Here, we study the Kuramoto model with inertia on simplicial complexes, merging two research domains. We develop an analytical framework in a mean-field setting using self-consistent equationsto describe the steady-state behavior, which reveals a prolonged hysteresis in the synchronization profile. Inertia and triadic interaction strength exhibit isolated influence on system dynamics by predominantly governing, respectively, the forward and backward transition points. This paper sets a paradigm to deepen our understanding of real-world complex systems such as power grids modeled as the Kuramoto model with inertia.

Weakly nonlinear analysis of thermoacoustic oscillations in can-annular combustors

Can-annular combustors feature clusters of thermoacoustic eigenvalues, which originate from the weak acoustic coupling between $N$ identical cans at the downstream end. When instabilities occur, one needs to consider the nonlinear interaction between all $N$ modes in the unstable cluster in order to predict the steady-state behaviour. A nonlinear reduced-order model for the analysis of this phenomenon is developed, based on the balance equations for acoustic mass, momentum and energy. Its linearisation yields explicit expressions for the $N$ complex-valued eigenfrequencies that form a cluster. To treat the nonlinear equations semianalytically, a Galerkin projection is performed, resulting in a nonlinear system of $N$ coupled oscillators. Each oscillator represents the dynamics of a global mode that oscillates in the whole can-annular combustor. The analytical expressions of the equations reveal how the geometrical and thermofluid parameters affect the thermoacoustic response of the system. To gain further insights, the method of averaging is applied to obtain equations for the slow-time dynamics of the amplitude and phase of each mode. The averaged system, whose solutions compare very well with those of the full oscillator equations, is shown to be able to predict complex transient dynamics. A variety of dynamical states are identified in the steady-state oscillatory regime, including push–push (in-phase) and spinning oscillations. Notably, the averaged equations are able to predict the existence of synchronised states. These states occur when the frequencies of two (or more) unstable modes with nominally different frequencies lock onto a common frequency as a result of nonlinear interactions.